A transcriptional cycling model recapitulates chromatin-dependent features of noisy inducible transcription

• Published in: PLoS computational biology 2022-09, Vol.18 (9), p.e1010152-e1010152
• Main Authors: Bullock, M. Elise, Moreno-Martinez, Nataly, Miller-Jensen, Kathryn
• Format: Article
• Language: English
• Subjects: Analysis; Biological activity; Biology and life sciences; Bursting; Chromatin; Chromatin remodeling; Cycles; Drug resistance; Gene expression; Genetic transcription; Heterogeneity; HIV; Human immunodeficiency virus; Mathematical models; Medicine and Health Sciences; NF-κB protein; Parameters; Properties; Proteins; RNA polymerase; Simulation; Transcription activation; Tumor necrosis factor-TNF; Viruses
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1010152

Activation of gene expression in response to environmental cues results in substantial phenotypic heterogeneity between cells that can impact a wide range of outcomes including differentiation, viral activation, and drug resistance. An important source of gene expression noise is transcriptional bursting, or the process by which transcripts are produced during infrequent bursts of promoter activity. Chromatin accessibility impacts transcriptional bursting by regulating the assembly of transcription factor and polymerase complexes on promoters, suggesting that the effect of an activating signal on transcriptional noise will depend on the initial chromatin state at the promoter. To explore this possibility, we simulated transcriptional activation using a transcriptional cycling model with three promoter states that represent chromatin remodeling, polymerase binding and pause release. We initiated this model over a large parameter range representing target genes with different chromatin environments, and found that, upon increasing the polymerase pause release rate to activate transcription, changes in gene expression noise varied significantly across initial promoter states. This model captured phenotypic differences in activation of latent HIV viruses integrated at different chromatin locations and mediated by the transcription factor NF-κB. Activating transcription in the model via increasing one or more of the transcript production rates, as occurs following NF-κB activation, reproduced experimentally measured transcript distributions for four different latent HIV viruses, as well as the bimodal pattern of HIV protein expression that leads to a subset of reactivated virus. Importantly, the parameter ‘activation path’ differentially affected gene expression noise, and ultimately viral activation, in line with experimental observations. This work demonstrates how upstream signaling pathways can be connected to biological processes that underlie transcriptional bursting, resulting in target gene-specific noise profiles following stimulation of a single upstream pathway.